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ICIAR
2007
Springer

Solving the Inverse Problem of Image Zooming Using "Self-Examples"

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Solving the Inverse Problem of Image Zooming Using "Self-Examples"
Abstract. In this paper we present a novel single-frame image zooming technique based on so-called “self-examples”. Our method combines the ideas of fractal-based image zooming, example-based zooming, and nonlocal-means image denoising in a consistent and improved framework. In Bayesian terms, this example-based zooming technique targets the MMSE estimate by learning the posterior directly from examples taken from the image itself at a different scale, similar to fractal-based techniques. The examples are weighted according to a scheme introduced by Buades et al. to perform nonlocal-means image denoising. Finally, various computational issues are addressed and some results of this image zooming method applied to natural images are presented.
Mehran Ebrahimi, Edward R. Vrscay
Added 08 Jun 2010
Updated 08 Jun 2010
Type Conference
Year 2007
Where ICIAR
Authors Mehran Ebrahimi, Edward R. Vrscay
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